Alternate oscillations of Martian hydrogen and oxygen upper atmospheres during a major dust storm

Dust storms on Mars play a role in transporting water from its lower to upper atmosphere, seasonally enhancing hydrogen escape. However, it remains unclear how water is diurnally transported during a dust storm and how its elements, hydrogen and oxygen, are subsequently influenced in the upper atmosphere. Here, we use multi-spacecraft and space telescope observations obtained during a major dust storm in Mars Year 33 to show that hydrogen abundance in the upper atmosphere gradually increases because of water supply above an altitude of 60 km, while oxygen abundance temporarily decreases via water ice absorption, catalytic loss, or downward transportation. Additionally, atmospheric waves modulate dust and water transportations, causing alternate oscillations of hydrogen and oxygen abundances in the upper atmosphere. If dust- and wave-driven couplings of the Martian lower and upper atmospheres are common in dust storms, with increasing escape of hydrogen, oxygen will less efficiently escape from the upper atmosphere, leading to a more oxidized atmosphere. These findings provide insights regarding Mars’ water loss history and its redox state, which are crucial for understanding the Martian habitable environment.


REVIEWER COMMENTS
Reviewer #1 (Remarks to the Author): Alternate oscillations of Martian hydrogen and oxygen upper atmospheres during a major dust storm Masunaga et al. submitted to Nature Communications This paper reports observations of the upper atmosphere of Mars with the Hisaki mission that shows the change in densities of H and O during a PEDE dust storm. Data from other spacecraft are shown to track the changes in the atmosphere and progression of the dust storm. The authors conclude that there are contrasting changes, with the H density increasing and O density decreasing, and that there are oscillations in these densities consistent with the time scale for baroclinic waves in the atmosphere. They go on to discuss the change in oxidation state of the overall atmosphere due to an imbalance of H and O loss to space.
Overall the paper is well written and interesting to read. The presentation of Hisaki data is new to the study of the 2018 PEDE, whereas other data on this event have been previously published. The identification of the oscillations appears to be solid, and the discussion of the implications is interesting. The identification of an increase in H density supports earlier reports of this, and the discussion of possible changes in oxidation state of the atmosphere is interesting if not overly well established. One feature of the Hisaki data is that the measurements give a global average of the emissions, whereas other spacecraft at Mars get point by point data. This can be an advantage in analyzing the PEDE event, which was a global dust storm, in deriving the global atmospheric response. One question I have is that in the Elrod paper there appear oscillations in the NGIMS O density values between LS 190 -240, and I wonder if the authors could analyze those data to further develop their presentation of this phenomenon. If the oscillations are real they would be expected to appear in both datasets, and the NGIMS data have much better time sampling.
One problem with this paper is that the changes in O density are not convincing. In Fig. 2 the slow increase in H is clearly seen, whereas for the O 1304 and 1356 emissions there is not a clear longterm trend either up or down. The main feature of those emissions is the oscillation that the authors analyze, which is well established from the Hisaki data. The 1304 emission shows a long term slow increase, with a high value just after the PEDE commencement and then a few low points. The problem is that these changes are 2-3 sigma from the plotted error bars, consistent with the discussed oscillation (i.e. not unique to the PEDE), and not supported by a long term decrease. The decrease in O during the PEDE is well established from the data published from the MAVEN NGIMS experiment, and the authors could refer to that for support for changes in O density and to better characterize those changes.
For changes in the O density, the 1304 emission is a better indicator of the O density than 1356. The 1304 emission is produced mainly by resonant scattering of solar emission while the 1356 is produced mainly by electron collisions, and while the solar 1304 flux can be measured the electron density is not well known. In this case the 1304 can be related to O density while more information is needed to derive density from 1356.
The Nature editor has asked for an evaluation of the significance of this work, and the extent to which it is new. The main results from measurements of the 2018 PEDE have been published before, and several papers are referenced in this work. The new results presented in this paper are mainly the Hisaki data and also more data from MCS (I am not aware of how much of this data has been previously published). Overall I have to describe this paper as an incremental improvement on our understanding of the atmospheric response to the 2018 PEDE, rather than a ground-breaking new direction of research.
The manuscript titled "Alternate oscillations of Martian hydrogen and oxygen upper atmosphere during a major dust storm" by Masunaga et al. presented multi-instruments data to show the effect of a dust storm on Martian atmosphere evolution.
The results are compelling and significant in the field of Martian atmosphere evolution given the evidence of dust-driven variability in the upper atmosphere and coupling between the lower atmosphere via the wave activities. The use of wave activity and observed oscillations in the emissions to deduce the time scale of dust impact on the atmospheric constituents is very novel and noteworthy.
I would recommend the publication of this study after some clarification.
1. The authors have referenced their previous study for Hisaki observations and data reduction. However, their published study only focused on OI 1304 and H Lyman Beta emission but did not mention OI 1356 A emission. Given the low disk brightness of OI 1356, it would be imperative to show the data for this emission in this study.
2. Line 125-126: Authors have indicated linear relation between OI 1356 brightness and Oxygen density, however electron impact on CO2 also contributes to this emission. Please explain.
Reviewer #3 (Remarks to the Author): This study describes the analysis of multi-spacecraft observations of the atmosphere of Mars in order to investigate the response of oxygen and hydrogen in the upper atmosphere as a consequence of dust storms in the lower and middle atmospheres. This study is in agreement with other studies showing that dust storms cause an increase in the exospheric H density and a decrease in the O density. In addition, the observations analysed in this study show an oscillating and anti-correlated pattern in the H and O brightness, which are attributed atmospheric waves being propagated from the surface. The results of this study have implications to understand the history of the Martian atmosphere and the role of atmospheric escape, and may be published after addressing the following comments.

Abstract
Line 25: slow dust transportation compared to atmospheric expansion --> The meaning of this sentence is unclear Line 28: oxygen decrease via downward transportation --> the main text appears to indicate that there are different scenarios that could explain the decrease in the O abundance in the exosphere.

Main text
Lines 42-45: The ascent of water to high altitudes is not only driven by dust storms, but also occurs every year close to during southern spring and summer (close to perihelion), even in the absence of major dust storms. Water increase during perihelion/dust storms is shown by Belyaev et al. (2021), andAlday et al. (2021) showed the expected seasonal variations in the H2O photolysis (i.e., H production), which are mainly driven by the Mars-Sun distance even in the absence of dust storms.
Lines 48-50: While H2O is the main reservoir of H in the atmosphere, the O in H2O just represents a very small part of the O reservoir in the atmosphere (95% CO2). Are the variations in the O upper atmosphere during dust storms caused by the H2O increase at high altitudes, or by the expansion of the whole atmosphere due to the intensified warming?
Line 68: rapidly --> rephrase with a more specific term. For example, something like: on a matter of X days Lines 70-74: From those plots it indeed looks that the cloud base was not situated at the 10-20 km level, which does not experience any change because of the dust storm. It looks as if the cloud layer was in the 20-40 km range, and the intensified warming because of the storm raised this level to the 60-80 km level. The increase in H2O at 40-60 km is very sharp, but also brief and transient, the increase in the 60-80 km level appears steadier. I think the interpretation is that the intensified warming in the middle atmosphere prevents the clouds to form at these lower levels, and water ice clouds are formed instead at much higher altitudes. I would consider including the 60-80 km level in Figure 1 to help this discussion.
Line 84: demonstrate --> show the time series… Line 87: as rapidly, similar to its behavior at lower altitudes --> As rapidly as at the lower altitudes?
Lines 89-94: What about dust acting as cloud condensation nuclei? The water will condense on the dust grains and therefore as the water ice opacity increases the dust opacity will decrease. Therefore, I am not sure that the interpretation of strong advection up to 60 km and then a decline above this altitude is entirely correct. The lag in the dust opacity might just indicate that water ice clouds are being formed at those altitudes.
Line 97: There is just one data point that exceeds 100 ppm at 40-60 km. In addition, the coverage of the SPICAM H2O profiles is quite sparse. It should be addressed in the text how representative the SPICAM profiles are for representing the whole atmosphere.
Lines 98-100: This interpretation that the increase in H2O in the middle atmosphere comes from a release of water by dust particles needs proof, and it might not be correct. The warmer temperatures due to the dust heating prevent the formation of water ice clouds, which essentially confine water vapour below the cloud level. In addition, the intensified atmospheric transport during dust storms increase advection and raise water to the upper layers (e.g., Heavens et al. Line 106: its --> this Lines 109-110: Is the Ly-beta emission optically thin? This will determine whether there is a linear relation between the density and the brightness.
Line 120: was much larger --> provide some estimates of the % of variation.
Line 122: Are the oxygen emissions optically thin? See comment above.
Line 125: in accordance with the observed atmospheric expansion --> is the increase or the decrease of O in accordance with the atmospheric expansion?
Lines 125-126: The decrease in the O densities during dust storms has been reported before and should be acknowledged in the text.
Lines 128: Does turbulence only affect the O transport, or all gaseous species?
Line 137: 130 km is the peak intensity --> this should be mentioned before making the calculation of the downward oxygen transportation.
Lines 126-146: It seems that several scenarios are suggested that could explain the decrease of O in the upper atmosphere. I suggest to re-organise this long paragraph to clearly highlight how these different scenarios would work. Lines 151-152: Here the analysis focuses on the dust storm. Are these oscillations also present in non-dusty periods? Lines 164-169: As mentioned in the text, the surface measurements are representative of a very specific location of the surface, while the airglow measurements encircle the whole planet, making their relation not that straightforward. Are similar oscillating patterns like these observed in the MCS temperature data at different altitude levels? The MCS dataset is likely more representative of the global behaviour of the atmosphere and will indicate how these waves propagate. Lines 181-184: This should be rephrased. While the transport timescale might be like that, H atoms formed at 20 km will mostly not make it to 130 km, since the timescale for photochemical H loss in the lower atmosphere is much shorter (Gonzalez-Galindo et al. 2005, JGR). In my opinion, it would be more intuitive to put the panels in the reversed order: 0-20 km and the highest altitude range the uppermost panel, as if they were all sharing the same y-axis.
Do the plotted lines include errorbars? They are averages, but they could include the standard deviation of all the averaged points to give an idea of the planet-wide variability.
I think this figure should also include the 60-80 km range for the plotted parameters to easily follow the discussion and interpretation of the climatological parameters.

Figure 2
The flux at 305A is not mentioned at all in the text.
As mentioned, some of the panels for the 60-80 km range could be included instead in Figure 1.
It must be indicated in the caption what the arrows represent. We would like to thank the reviewer for the helpful comments after the thorough reading of this manuscript. We have considered all the suggested comments and revised our manuscript.
Upon your request, we added MAVEN/NGIMS data to the analysis, which improved our interpretation and discussion. We also noticed that there were SPICAM water mixing ratio data (3 data points) at 80-90 km and added them to improve the discussion. Furthermore, we revised the texts and figures based on all reviewer comments. We would like to emphasize that, nevertheless, these changes did not affect our conclusion.
We describe our point-to-point responses to each comment below with the original comments in black and our response in blue. The line number in the reply refers to the revised manuscript with a track change.
Overall the paper is well written and interesting to read. The presentation of Hisaki data is new to the study of the 2018 PEDE, whereas other data on this event have been previously published. The identification of the oscillations appears to be solid, and the discussion of the implications is interesting. The identification of an increase in H density supports earlier reports of this, and the discussion of possible changes in oxidation state of the atmosphere is interesting if not overly well established. One feature of the Hisaki data is that the measurements give a global average of the emissions, whereas other spacecraft at Mars get point by point data. This can be an advantage in analyzing the PEDE event, which was a global dust storm, in deriving the global atmospheric response. One question I have is that in the Elrod paper there appear oscillations in the NGIMS O density values between LS 190 -240, and I wonder if the authors could analyze those data to further develop their presentation of this phenomenon. If the oscillations are real they would be expected to appear in both datasets, and the NGIMS data have much better time sampling.
Please let us clarify that we are not studying the 2018 PEDE event in this paper but a regional dust storm event (A-storm) in 2016. Nevertheless, we analyzed NGIMS data obtained in our observation period and revised the paper (lines 177-188).
Based on our NGIMS data analysis , O densities in three different altitudes overall showed similar variations to oxygen airglow variations. The O density exhibited a decrease by a factor of ~1.5 between the storm onset and Sep 12. After that, it gradually recovers to the original level. We also studied periodicities of the NGIMS data using the periodogram method ( Supplementary Fig. 2), and we found a 6.8-day periodicity. These consistencies between the in-situ NGIMS and entire disk Hisaki measurements suggest that the observed O variations were a global feature in the upper atmosphere of Mars.
One problem with this paper is that the changes in O density are not convincing. In Fig. 2 the slow increase in H is clearly seen, whereas for the O 1304 and 1356 emissions there is not a clear long-term trend either up or down. The main feature of those emissions is the oscillation that the authors analyze, which is well established from the Hisaki data. The 1304 emission shows a long term slow increase, with a high value just after the PEDE commencement and then a few low points. The problem is that these changes are 2-3 sigma from the plotted error bars, consistent with the discussed oscillation (i.e. not unique to the PEDE), and not supported by a long term decrease. The decrease in O during the PEDE is well established from the data published from the MAVEN NGIMS experiment, and the authors could refer to that for support for changes in O density and to better characterize those changes.
As described above, we found a factor of ~1. 5  For changes in the O density, the 1304 emission is a better indicator of the O density than 1356. The 1304 emission is produced mainly by resonant scattering of solar emission while the 1356 is produced mainly by electron collisions, and while the solar 1304 flux can be measured the electron density is not well known. In this case the 1304 can be related to O density while more information is needed to derive density from 1356.
The 1304 emission is not only excited by resonant scattering but also by photoelectron impact in the ionosphere. Therefore, this emission reflects the column density of cold oxygen atoms excited by photoelectron impact near 130 km altitude (ionospheric peak altitude) as well as hot oxygen atoms excited by resonant scattering at higher altitudes. In addition, the 1304 emission is optically very thick, so its brightness is not linearly correlated to column density. On the other hand, the 1356 emission is mainly exited by photoelectron impact on O atoms and this emission is spin-forbidden and thus optically thin. Thus, the 1356 emission rather provides information on oxygen column density near 130 km altitude (ionospheric peak altitude).
The Nature editor has asked for an evaluation of the significance of this work, and the extent to which it is new. The main results from measurements of the 2018 PEDE have been published before, and several papers are referenced in this work. The new results presented in this paper are mainly the Hisaki data and also more data from MCS (I am not aware of how much of this data has been previously published). Overall I have to describe this paper as an incremental improvement on our understanding of the atmospheric response to the 2018 PEDE, rather than a ground-breaking new direction of research.
Again, please let us clarify that we are not studying the 2018 PEDE event in this paper but a regional dust storm event (A-storm) in 2016. Although a PEDE event produces a drastic change in the Martian atmospheric condition, it only occurs every 3-4 Mars Years (6-8 Earth years) on average. On the other hand, major regional dust storms (A-, B-and C-storms) occur 3 times every Mars Year. Even though a regional dust storm does not cover the entire surface of Mars, our observation shows that it affects the upper atmosphere globally. If the dust-and wave-coupling effects on the upper atmosphere, and the atmospheric oxidation process that we suggested in this paper are common features in all regional dust storms, it is possible that the Martian atmosphere has been oxidized every Mars Year over a long period of Mars' history. In this context, regional dust storms provide a significant impact on the atmospheric evolution of Mars, and thus, our findings are crucial for understanding habitable environments on Mars.
Reviewer #2 (Remarks to the Author): The manuscript titled "Alternate oscillations of Martian hydrogen and oxygen upper atmosphere during a major dust storm" by Masunaga et al. presented multi-instruments data to show the effect of a dust storm on Martian atmosphere evolution.
The results are compelling and significant in the field of Martian atmosphere evolution given the evidence of dust-driven variability in the upper atmosphere and coupling between the lower atmosphere via the wave activities. The use of wave activity and observed oscillations in the emissions to deduce the time scale of dust impact on the atmospheric constituents is very novel and noteworthy.
I would recommend the publication of this study after some clarification.
We would like to thank the reviewer for the helpful comments after the thorough reading of this manuscript. We have considered all the suggested comments and revised our manuscript.
Upon a request from another referee, we added MAVEN/NGIMS data to the analysis, which improved our interpretation and discussion. We also noticed that there were SPICAM water mixing ratio data (3 data points) at 80-90 km and added them to improve the discussion. Furthermore, we revised the texts and figures based on all reviewer comments. We would like to emphasize that, nevertheless, these changes did not affect our conclusion.
We describe our point-to-point responses to each comment below with the original comments in black and our response in blue. The line number in the reply refers to the revised manuscript with a track change.
1. The authors have referenced their previous study for Hisaki observations and data reduction. However, their published study only focused on OI 1304 and H Lyman Beta emission but did not mention OI 1356 A emission. Given the low disk brightness of OI 1356, it would be imperative to show the data for this emission in this study.
We agree with the reviewer. We've decided to add examples of the OI 1356 spectrum as well as OI 1304 and HI Ly-beta in the Supplementary Figure. 2. Line 125-126: Authors have indicated linear relation between OI 1356 brightness and Oxygen density, however electron impact on CO2 also contributes to this emission. Please explain. Ritter et al. (2019), JGR, 10.1029/2019JA026669, the main contributor (95%) for the 1356 emission is electron impact on O, and electron impact on CO2 is a neglected source (5%). Additionally, the 1356 emission is optically thin. Therefore, we interpret the 1356 brightness as being correlated to oxygen (column) density.

According to MAVEN/IUVS observations by
Again, we would like to thank the reviewer for reading our manuscript carefully and giving helpful comments to make this paper's quality better. We hope that the revised manuscript is suitable for publication in Nature Communications.

Sincerely, Kei Masunaga
Reviewer #3 (Remarks to the Author): This study describes the analysis of multi-spacecraft observations of the atmosphere of Mars in order to investigate the response of oxygen and hydrogen in the upper atmosphere as a consequence of dust storms in the lower and middle atmospheres. This study is in agreement with other studies showing that dust storms cause an increase in the exospheric H density and a decrease in the O density. In addition, the observations analysed in this study show an oscillating and anti-correlated pattern in the H and O brightness, which are attributed atmospheric waves being propagated from the surface. The results of this study have implications to understand the history of the Martian atmosphere and the role of atmospheric escape, and may be published after addressing the following comments.
We would like to thank the reviewer for the helpful comments after the thorough reading of this manuscript. We have considered all the suggested comments and revised our manuscript.
Upon a request from another referee, we added MAVEN/NGIMS data to the analysis, which improved our interpretation and discussion. We also noticed that there were SPICAM water mixing ratio data (3 data points) at 80-90 km and added them to improve the discussion. Furthermore, we revised the texts and figures based on all reviewer comments. We would like to emphasize that, nevertheless, these changes did not affect our conclusion.
We describe our point-to-point responses to each comment below with the original comments in black and our response in blue. The line number in the reply refers to the revised manuscript with a track change.

Abstract
Line 25: slow dust transportation compared to atmospheric expansion --&gt; The meaning of this sentence is unclear We revised the text at line 28.
Line 28: oxygen decrease via downward transportation --&gt; the main text appears to indicate that there are different scenarios that could explain the decrease in the O abundance in the exosphere. We revised the text in lines 29-30.

Main text
Lines 42-45: The ascent of water to high altitudes is not only driven by dust storms, but also occurs every year close to during southern spring and summer (close to perihelion), even in the absence of major dust storms. Water increase during perihelion/dust storms is shown by Belyaev et al. (2021), andAlday et al. (2021) showed the expected seasonal variations in the H2O photolysis (i.e., H production), which are mainly driven by the Mars-Sun distance even in the absence of dust storms. We revised the texts at lines 46-51 and added Belyaev et al. (2021)  Line 68: rapidly --&gt; rephrase with a more specific term. For example, something like: on a matter of X days We revised the texts at line 79.
Lines 70-74: From those plots it indeed looks that the cloud base was not situated at the 10-20 km level, which does not experience any change because of the dust storm. It looks as if the cloud layer was in the 20-40 km range, and the intensified warming because of the storm raised this level to the 60-80 km level. The increase in H2O at 40-60 km is very sharp, but also brief and transient, the increase in the 60-80 km level appears steadier. I think the interpretation is that the intensified warming in the middle atmosphere prevents the clouds to form at these lower levels, and water ice clouds are formed instead at much higher altitudes. I would consider including the 60-80 km level in Figure 1 to help this discussion. We added the data of 60-80 km in Figure 1.
Line 87: as rapidly, similar to its behavior at lower altitudes --&gt; As rapidly as at the lower altitudes? Fixed.
Lines 89-94: What about dust acting as cloud condensation nuclei? The water will condense on the dust grains and therefore as the water ice opacity increases the dust opacity will decrease. Therefore, I am not sure that the interpretation of strong advection up to 60 km and then a decline above this altitude is entirely correct. The lag in the dust opacity might just indicate that water ice clouds are being formed at those altitudes.

The reviewer's opinion might be true, and we revised the text in lines 113-118.
Line 97: There is just one data point that exceeds 100 ppm at 40-60 km. In addition, the coverage of the SPICAM H2O profiles is quite sparse. It should be addressed in the text how representative the SPICAM profiles are for representing the whole atmosphere. It was a mistake. We meant 60-90 km and revised the text at line 112. (Please note that we added the 80-90 km data.) Regarding the SPICAM data coverage, the SPICAM observations did not cover whole latitude and longitude (see Supplementary Fig. 2). Nevertheless, the increasing trend of H2O mixing ratio is similar between northern and southern hemispheres in 20-40 km and 40-60 km altitude ranges. In the 60-80 km and 80-90 km ranges, we only cover the southern hemisphere, but the increasing tendency resembles those in the lower altitude. With that, we assume that SPICAM measurements are representative of the whole atmosphere. We added the explanation on lines 108-110.
Lines 98-100: This interpretation that the increase in H2O in the middle atmosphere comes from a release of water by dust particles needs proof, and it might not be correct. The warmer temperatures due to the dust heating prevent the formation of water ice clouds, which essentially confine water vapour below the cloud level. In addition, the intensified atmospheric transport during dust storms increase advection and raise water to the upper layers (e.g., Heavens et al. 2019, GRL;Shaposhnikov et al. 2019, GRL). We removed this interpretation because there was no proof.

Line 106: its --&gt; this Done
Lines 109-110: Is the Ly-beta emission optically thin? This will determine whether there is a linear relation between the density and the brightness. Although it is not straightforward to estimate the optical depth from the disk (and limb) average data of Hisaki, the Ly-β emission is optically thick based on brightness value and the line-center scattering cross section (Masunaga et al., 2020). However, with the Chemberlain model and exospheric parameters close to our observation period in Chaffin et al. (2018), it turned out that Ly-β optical depth at exobase altitude (200 km) is near unity (1.2) on the disk but much larger than that on the limb. Thus, we can assume that our Ly-β brightness variation would change proportionally to variations in brightness on the disk rather than limb. So, we can assume that although the Ly-β brightness does not exhibit a linear relation to the column density near the limb, our observation most likely reflect the column density above 200 km altitude on the disk. We revised the text at lines 135-138.
Line 120: was much larger --&gt; provide some estimates of the % of variation. The variation level is 20-50% as revealed in the residual analysis later in the text. Because we have not discussed the variation level at this point, we decided not to add the value here.
Line 122: Are the oxygen emissions optically thin? See comment above. The 1304 emission is optically thick (Ritter et al., 2019) and its optical depth is much larger than Ly-β (Masunaga et al., 2020). On the other hand, 1356 is optically thin (Ritter et al., 2019 Ly-beta optical depth on the disk  We removed this discussion due to changes in our interpretation but added a new discussion about the time scales of hydrogen atmosphere and high-altitude water at lines 138-161. Lines 181-184: This should be rephrased. While the transport timescale might be like that, H atoms formed at 20 km will mostly not make it to 130 km, since the timescale for photochemical H loss in the lower atmosphere is much shorter (Gonzalez-Galindo et al. 2005, JGR). We removed this discussion due to changes in our interpretation.

Figure 1
In my opinion, it would be more intuitive to put the panels in the reversed order: 0-20 km and the highest altitude range the uppermost panel, as if they were all sharing the same y-axis.
We have fixed the figure as the reviewer suggested. We also added the 60-80 km data.
Do the plotted lines include errorbars? They are averages, but they could include the standard deviation of all the averaged points to give an idea of the planet-wide variability. Figures 1  (and 2), but the wide y-range makes it difficult for readers to see the average variations that we want to discuss in this paper. Additionally, because each average data point is an average value calculated by data points within LT 11-13h of a Martian day, a large standard deviation means that the data highly varies within a Martian day, suggesting that wave activities shorter than a Martian day exist. Because we focus on longer time scale (i.e., 6-8 day) variations in this paper, such a short time scale variation is out of our scope, and conclude that this does not affect our conclusion. Therefore, we decided to show the average variations without standard deviations in Figures 1 (and 2).

As seen from Supplementary Figs. 1 and 7, the point-by-point data (grey colored dots) show large variations, resulting in large standard deviations. We tried to include the standard deviation in
I think this figure should also include the 60-80 km range for the plotted parameters to easily follow the discussion and interpretation of the climatological parameters.
We added the 60-80 km range in Figure 1 and changed the order.

Figure 2
The flux at 305A is not mentioned at all in the text. We added an explanation at line 165.
As mentioned, some of the panels for the 60-80 km range could be included instead in Figure 1.

Done.
It must be indicated in the caption what the arrows represent.
We removed these arrows due to changes in our interpretation.

Figure 3
Include errorbars in the Residual brightness. Done.

Include the 1304 A emission and search for similar patterns in MCS data.
Because the OI 1304 emission is optically very thick (tau>30), it is inappropriate to discuss column density variation. Thus, we decided not to include the 1304 variation here.

Methods
Lines 333-340: I guess that this dataset relies on the limb-viewing observations. Indicate the number of observations and coverage used in this study. Line 355: has collected a comprehensive&#x2026; Fixed.

We added the geometry information of MCS limb observations in 20-40 km altitude in Supplementary
Line 353: For SPICAM please also indicate the coverage and number of observations. We added the SPICAM's geometry information in Supplementary Fig. 2 (2017) -It would be good to state somewhere why Ly-beta was reported rather than the much brighter Ly-alpha. I am guessing it is because of the high background of geocoronal emission from low earth orbit, but it should be explained.
-It is stated that since Ly-beta roughly doubled the density likely doubled. It is more likely that while the density increased, the higher temp. in the upper atmosphere broadened the H line reflecting more solar emission, and the measured increase in brightness was due to a combination of these effects.
-For the record the 1304 emission is "mainly" produced by resonant scattering although there is a component from electron collisional excitation. This is supported by MAVEN observations of the 1304 triplet line ratio, which is consistent with resonant scattering and not electron collisions. As the authors agree the 1356 emission is excited by electron collisions, so the 1304 and 1356 emissions reveal different processes. Nonetheless they seem to track each other in the Hisaki data, at least well enough to not quibble about the difference. Overall the authors have been highly responsive to the comments from this referee on the original submitted manuscript. They have pulled up the MAVEN data from the same time period to compare global and local measurements, and apologies for confusing the dust storms in 2016 and 2019 in my original comments. As the authors point out the conclusions of the paper are not affected by the year of the dust storm, although the 2016 event has been much less reported upon which increases the significance of the present work.

RESPONSE TO REVIEWERS' COMMENTS
At this point I think that the authors have done their job in revising the paper and defending their conclusions. It is an interesting and important result of interest to a broad range of researchers, and worthy of acceptance in Nat. Comm.
We would like to thank again the reviewer for reading the revised paper and providing comments to improve our manuscript. We have considered all the suggested comments and revised our manuscript. We describe our point-to-point responses to each comment below with the original comments in black and our response in blue. The line number in the reply refers to the revised manuscript with a track change.
Having said that, here are a few specific points for the authors to consider before the paper is published:  (2017) We added the above paper to the reference list.
-It would be good to state somewhere why Ly-beta was reported rather than the much brighter Lyalpha. I am guessing it is because of the high background of geocoronal emission from low earth orbit, but it should be explained.
As mentioned in Masunaga et al. (2020), the detector's sensitivity near the wavelength of Ly-alpha significantly degraded in the middle of the mission, whose possible cause was recently identified as the constant exposure to the extremely strong Ly-alpha emissions of geocorona and planetary atmospheres. So, Ly-alpha data is currently available only at the beginning of the mission (Kuwabara et al., 2017, JGR space phys., doi:10.1002. The detector near Ly-beta, on the other hand, did not experience such a degradation because Ly-beta emission was much weaker than Ly-alpha. In this paper, therefore, we used the Ly-beta data instead of Lyman-alpha. We added a brief explanation about the non-use of Ly-alpha data in the Method section (at lines 295-300).
-It is stated that since Ly-beta roughly doubled the density likely doubled. It is more likely that while the density increased, the higher temp. in the upper atmosphere broadened the H line reflecting more solar emission, and the measured increase in brightness was due to a combination of these effects.
First, we meant that the "column density" doubled, so we revised the texts at line 140.
Second, if we understood this comment correctly, the reviewer's concern was if the exospheric temperature affected the Ly-beta brightness. We are actually not able to constrain whether density or temperature affected the column density directly from the disk-average measurements of Hisaki, but we can roughly estimate it. The airglow brightness can be roughly estimated by B = gN/1e6 (B is brightness in Rayleigh, g is g-factor in s -1 , and N is column density in cm -2 -For the record the 1304 emission is "mainly" produced by resonant scattering although there is a component from electron collisional excitation. This is supported by MAVEN observations of the 1304 triplet line ratio, which is consistent with resonant scattering and not electron collisions. As the authors agree the 1356 emission is excited by electron collisions, so the 1304 and 1356 emissions reveal different processes. Nonetheless they seem to track each other in the Hisaki data, at least well enough to not quibble about the difference.